Subscribe via email

Sign up with your email address to receive blog posts via email.

Email Address

I respect your privacy.

Thank you!

This website covers knowledge management, personal effectiveness, theory of constraints, amongst other topics. Opinions expressed here are strictly those of the owner, Jack Vinson, and those of the commenters.

Mar 20 Another view on Data, Information, Knowledge

Data, information and knowledge can be approached from many directions. This paper focuses on the limits of the traditional economic theory approach and rounds out the concepts with views from sociology, information theory and information physics.

Abstract: Economists make the unarticulated assumption that information is something that stands apart from and is independent of processors of information and their inherent characteristics. We argue that they need to revisit the distinctions they have drawn between data, information and knowledge. While some associate information with data, others associate it with knowledge. But since few readily associate data with knowledge, this suggests too loose a conceptualisation of the term 'information'. We argue that the difference between data, information and knowledge is in fact crucial. Information theory and the physics of information provide us with useful insights with which to build an economics of information appropriate to the needs of the emerging information economy.

The authors review a range of literature to help frame their discussion of the differences between data, information and knowledge. As noted in the abstract, their focus is on how economic theory (value or utility of data, information and/or knowledge) talks about the differences. Essentially, they say, economic theory does very little with the value of information or knowledge, particularly when you take into account context and different viewpoints. To help rectify this, the authors call on the ideas found in a number of other research fields.

They look at sociology and organization theory to help set the stage for their further discussion on meaning, semantics, common knowledge and other assumptions that are made in the economic theories. Within this section, the authors discuss the concept of an individual's history as heavily influencing how and what they filter out of the incoming streams of data. What an individual perceives as being important is very dependent on their history, on their context. And for a group of people, their understanding of information depends greatly on their shared context, an idea that we see repeatedly when discussing knowledge management and the ability of KM project to succeed.

They bring in a discussion of information theory, which tends to be quite strict in its handling of information only -- and typically only the transmission of that information. They acknowledge that the traditional views in this arena essentially ignore any differentiation between data, information, and knowledge. This field is really only concerned with information (or data) transmission and not in the underlying data represented by the transmissions or whether the transmissions have their desired effect on the other end of the line.

Information theory is a prelude to a discussion of information physics, which is a new-to-me area of study. This gets into quantum information theory, which quickly gets me into trouble. The discussion crosses borders between physics and information that I "get," but I don't know enough about to make any valuable comments. They have some fun discussing how a Maxwell's Demon might operate in the information space.

This leads to a discussion of thermodynamics, focused on the 2nd Law and Entropy, the principle that every action irreversibly bleeds off some energy. In the D-I-K world, the authors draw on this idea of Information Physics to talk about entropy and what gets lost -- erased -- when looking at differences within each of the elements. This is from the summary:

Developing further the difference between data, information and knowledge, data generates thermodynamic entropy, which we shall label entropy 1. It involves the erasure of differences between physical states. Information, by contrast, generates Shannon entropy, which we shall label entropy 2. It involves the erasure of differences between symbols. The difference between physical states might well be maintained, but the form given to such states no longer yield unambiguous symbols. Finally, knowledge generates cognitive entropy, which we shall label entropy 3. It involves the erasure of differences between the possible contexts required for the interpretation of either states or symbols.

So, finally, what view of data-information-knowledge is presented? As with the paper, their view seems to be multifaceted. Early in the paper, they work with a description that has to do with how people process data, information and knowledge. The world continuously bombards us (or any "agent") with stimuli. These are filtered by our "sensors," leaving us with incoming data. Stimuli that cannot be perceived by our human sensors (UV light, very high frequency sound, etc) are never part of the incoming data. These data are then processed by conceptual filters to extract information, which can then feed our knowledge stores and enable us to act and/or modify those knowledge stores. Our actions - or the actions of any agent - can potentially modify the external stimuli, yielding new data and information as it is filtered. Their goal here is to show how data, information and knowledge each have different utility within an agent.

Later in the paper, the discussion is geared around the information theory and information physics approach. This was less clear to me, but the differences were more associated with the way entropy acts within each area, as described above.

For another view, I happened to come across Don Clark's nice visualization of the distinction as a 2x2 matrix which embed the ideas of speed vs. "stickiness" (viscosity - a Davenport Working Knowledge term) and context vs. single-mindedness. He also layers "wisdom" behind this matrix, growing out of the knowledge quadrant.

Note: UOC is Universitat Oberta de Catalunya or Open University of Catalonia is based in Barcelona, but offers distance education to a wide audience. Their website is in Spanish, Catalan and English.

Related Posts

This blog is about knowledge management, personal effectiveness, theory of constraints and other topics. Opinions expressed here are strictly those of the owner, Jack Vinson, and those of the commenters.